scholarly journals Impact of connected vehicle guidance information on network-wide average travel time

2017 ◽  
Vol 9 (1) ◽  
pp. 168781401668335 ◽  
Author(s):  
Jiangfeng Wang ◽  
Jiarun Lv ◽  
Qian Zhang ◽  
Xuedong Yan
Keyword(s):  
Travel Time ◽  
Data Exchange ◽  
Positive Impact ◽  
Penetration Rate ◽  
Transportation Systems ◽  
Time Variability ◽  
Connected Vehicle ◽  
Vehicle Guidance ◽  
Average Travel Time ◽  
The Impact

With the emergence of connected vehicle technologies, the potential positive impact of connected vehicle guidance on mobility has become a research hotspot by data exchange among vehicles, infrastructure, and mobile devices. This study is focused on micro-modeling and quantitatively evaluating the impact of connected vehicle guidance on network-wide travel time by introducing various affecting factors. To evaluate the benefits of connected vehicle guidance, a simulation architecture based on one engine is proposed representing the connected vehicle–enabled virtual world, and connected vehicle route guidance scenario is established through the development of communication agent and intelligent transportation systems agents using connected vehicle application programming interface considering the communication properties, such as path loss and transmission power. The impact of connected vehicle guidance on network-wide travel time is analyzed by comparing with non-connected vehicle guidance in response to different market penetration rate, following rate, and congestion level. The simulation results explore that average network-wide travel time in connected vehicle guidance shows a significant reduction versus that in non–connected vehicle guidance. Average network-wide travel time in connected vehicle guidance have an increase of 42.23% comparing to that in non-connected vehicle guidance, and average travel time variability (represented by the coefficient of variance) increases as the travel time increases. Other vital findings include that higher penetration rate and following rate generate bigger savings of average network-wide travel time. The savings of average network-wide travel time increase from 17% to 38% according to different congestion levels, and savings of average travel time in more serious congestion have a more obvious improvement for the same penetration rate or following rate.

Travel-Time Reliability as a Measure of Service

2003 ◽  
Vol 1855 (1) ◽  
pp. 74-79 ◽  
Author(s):  
Chao Chen ◽  
Alexander Skabardonis ◽  
Pravin Varaiya
Keyword(s):  
Los Angeles ◽  
Travel Time ◽  
Intelligent Transportation Systems ◽  
Transportation Systems ◽  
Time Variability ◽  
Travel Time Reliability ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Average Travel Time ◽  
Travel Time Variability

Statistics from a corridor along Interstate 5 in Los Angeles show that average travel time and travel-time variability are meaningful measures of freeway performance. Variability of travel time is an important measure of service quality for travelers. Travel time can be used to quantify the effect of incidents, and incident information can help reduce travel-time uncertainty. Predictability of travel time is a measure of the benefits of intelligent transportation systems. These measures differ from those defined in the Highway Capacity Manual and other aggregate measures of delay.

Parameter Sensitivity Analysis of a Cooperative Dynamic Bus Lane System With Connected Vehicles

2021 ◽  
pp. 036119812110357
Author(s):  
Meng Xie ◽  
Michael Winsor ◽  
Tao Ma ◽  
Andreas Rau ◽  
Fritz Busch ◽  
...  
Keyword(s):  
Travel Time ◽  
Transition Period ◽  
Penetration Rate ◽  
Simulation Models ◽  
Driving Behavior ◽  
Connected Vehicles ◽  
Microscopic Simulation ◽  
Communication Range ◽  
Bus Lane ◽  
The Impact

This paper aims to evaluate the sensitivity of the proposed cooperative dynamic bus lane system with microscopic traffic simulation models. The system creates a flexible bus priority lane that is only activated on demand at an appropriate time with advanced information and communication technologies, which can maximize the use of road space. A decentralized multi-lane cooperative algorithm is developed and implemented in a microscopic simulation environment to coordinate lane changing, gap acceptance, and car-following driving behavior for the connected vehicles (CVs) on the bus lane and the adjacent lanes. The key parameters for the sensitivity study include the penetration rate and communication range of CVs, considering the transition period and gradual uptake of CVs. Multiple scenarios are developed and compared to analyze the impact of key parameters on the system’s performance, such as total saved travel time of all passengers and travel time variation among buses and private vehicles. The microscopic simulation models showed that the cooperative dynamic bus lane system is significantly sensitive to the variations of the penetration rate and the communication range in a congested traffic state. With a CV system and a communication range of 150 m, buses obtain maximum benefits with minimal impacts on private vehicles in the study simulation. The safety concerns induced by cooperative driving behavior are also discussed in this paper.

scholarly journals Examining the Impact of Adverse Weather on Travel Time Reliability of Urban Corridors in Shanghai

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yajie Zou ◽  
Ting Zhu ◽  
Yifan Xie ◽  
Linbo Li ◽  
Ying Chen
Keyword(s):  
Travel Time ◽  
Weather Condition ◽  
Time Of Day ◽  
Weather Data ◽  
Time Variability ◽  
Travel Time Reliability ◽  
Time Data ◽  
Adverse Weather Condition ◽  
Adverse Weather ◽  
The Impact

Travel time reliability (TTR) is widely used to evaluate transportation system performance. Adverse weather condition is an important factor for affecting TTR, which can cause traffic congestions and crashes. Considering the traffic characteristics under different traffic conditions, it is necessary to explore the impact of adverse weather on TTR under different conditions. This study conducted an empirical travel time analysis using traffic data and weather data collected on Yanan corridor in Shanghai. The travel time distributions were analysed under different roadway types, weather, and time of day. Four typical scenarios (i.e., peak hours and off-peak hours on elevated expressway, peak hours and off-peak hours on arterial road) were considered in the TTR analysis. Four measures were calculated to evaluate the impact of adverse weather on TTR. The results indicated that the lognormal distribution is preferred for describing the travel time data. Compared with off-peak hours, the impact of adverse weather is more significant for peak hours. The travel time variability, buffer time index, misery index, and frequency of congestion increased by an average of 29%, 19%, 22%, and 63%, respectively, under the adverse weather condition. The findings in this study are useful for transportation management agencies to design traffic control strategies when adverse weather occurs.

Illustrating the Monetary Impact of Transportation Projects/Alternatives using the Values of Travel Time and Travel Time Reliability

2018 ◽  
Vol 2672 (51) ◽  
pp. 88-98 ◽  
Author(s):  
Venkata R. Duddu ◽  
Srinivas S. Pulugurtha ◽  
Praveena Penmetsa
Keyword(s):  
Travel Time ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Transportation Systems ◽  
Travel Time Reliability ◽  
Benefit Analysis ◽  
Transportation Projects ◽  
Travel Time Savings ◽  
Time Savings ◽  
The Impact

State agencies, regional agencies, cities, towns, and local municipalities design and maintain transportation systems for the benefit of users by improving mobility, reducing travel time, and enhancing safety. Cost–benefit analysis based on travel time savings and the value of reliability helps these agencies in prioritizing transportation projects or when evaluating transportation alternatives. This paper illustrates the use of monetary values of travel time savings and travel time reliability, computed for the state of North Carolina, to help assess the impact of transportation projects or alternatives. The results obtained indicate that, based on the illustration of the effect and impact of various transportation projects or alternatives, both improved travel time and reliability on roads yield significant monetary benefits. However, from cost–benefit analysis, it is observed that greater benefits can be achieved through improved reliability compared with benefits from a decrease in travel time for a given section of road.

scholarly journals The Impact of Transit Oriented Development Apartment Building to Pedestrian's Level of Service in Pondok Cina Station Using Microscopic Modeling

2019 ◽  
Vol 278 ◽  
pp. 05003
Author(s):  
Randy Asad Pradana ◽  
R. Jachrizal Sumabrata
Keyword(s):  
Travel Time ◽  
Positive Impact ◽  
Service Level ◽  
Field Analysis ◽  
Level Of Service ◽  
Transit Oriented Development ◽  
Total Change ◽  
Result Show ◽  
Microscopic Modeling ◽  
The Impact

The construction of the TOD apartment at the Pondok Cina Station will have an impact on the level of service at the venue. This has a positive impact because there is an increase in KRL users, but it also has the potential to cause problems due to the increased volume. This study aims to analyze the impact of TOD station Pondok Cina apartment development on station service level in 2022 condition and find the best solution to improve service level. The station model is created using PTV VISWALK 10. Validation testing is needed to determine the model is acceptable or not by comparing the model results and actual conditions in the field. Analysis of service level using HCM as a reference. There are several models performed, such as the condition of existing year 2018, condition year 2022 without apartment, condition 2022 with apartment, and alternative condition. Alternative conditions of total change in Pondok Cina station. After the simulation, see the performance of all models based on service level and travel time. The result show given the influence of the apartment, if nothing is done then the level of service worsens from LOS B to LOS E while travel time increases drastically from 78 seconds to 429 seconds by 2022.

scholarly journals Competing Risks Models for the Assessment of Intelligent Transportation Systems Devices: A Case Study for Connected and Autonomous Vehicle Applications

2020 ◽  
Vol 5 (3) ◽  
pp. 30 ◽  
Author(s):  
Sylvester Inkoom ◽  
John Sobanjo ◽  
Eric Chicken
Keyword(s):  
Wireless Communication ◽  
Communication Networks ◽  
Competing Risks ◽  
Communication Systems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Hazard Ratio ◽  
Connected Vehicle ◽  
Average Hazard Ratio ◽  
The Impact

Intelligent transportation system (ITS) has become a crucial section of transportation and traffic management systems in the past decades. As a result, transportation agencies keep improving the quality of transportation infrastructure management information for accessibility and security of transportation networks. The goal of this paper is to evaluate the impact of two competing risks: “natural deterioration” of ITS devices and hurricane-induced failure of the same components. The major devices employed in the architecture of this paper include closed circuit television (CCTV) cameras, automatic vehicle identification (AVI) systems, dynamic message signals (DMS), wireless communication systems and DMS towers. From the findings, it was evident that as ITS infrastructure devices age, the contribution of Hurricane Category 3 as a competing failure risk is higher and significant compared to the natural deterioration of devices. Hurricane Category 3 failure vs. natural deterioration indicated an average hazard ratio of 1.5 for CCTV, AVI and wireless communications systems and an average hazard ratio of 2.3 for DMS, DMS towers and portable DMS. The proportional hazard ratios of the Hurricane Category 1 compared to the devices was estimated as <0.001 and that of Hurricane Category 2 < 0.5, demonstrating the lesser impact of the Hurricane Categories 1 and 2. It is expedient to envisage and forecast the impact of hurricanes on the failure of wireless communication networks, vehicle detection systems and other message signals, in order to prevent vehicle to infrastructure connection disruption, especially for autonomous and connected vehicle systems.

scholarly journals The Displacement of Santiago de Chile’s Downtown during 1990–2015: Travel Time Effects on Eradicated Population

2019 ◽  
Vol 12 (1) ◽  
pp. 289 ◽  
Author(s):  
Gonzalo Suazo-Vecino ◽  
Juan Carlos Muñoz ◽  
Luis Fuentes Arce
Keyword(s):  
Travel Time ◽  
Surface Area ◽  
Low Income ◽  
Central Area ◽  
Time Effects ◽  
Socioeconomic Groups ◽  
Santiago De Chile ◽  
Average Travel Time ◽  
The Impact ◽  
The City

The center of activities of Santiago de Chile has been continuously evolving towards the eastern part of the city, where the most affluent residents live. This paper characterizes the direction and magnitude of this evolution through an indicator stating how much the built surface area for service purposes grows in different areas in the city. To identify the impact of this evolution, we compare residents’ travel-time distributions from different sectors in the city to the central area. This travel-time comparison is focused on the sectors where informal settlements were massively eradicated between 1978–1985 and those areas where the settlements were relocated. This analysis show that this policy and the consequent evolution of the city were detrimental to the affected families, significantly increasing average travel time to the extended center of the city and inequality among different socioeconomic groups in the city. Although the phenomenon is quite visible to everyone, it has not received any policy reaction from the authority. These findings suggest that middle and low-income sectors would benefit if policies driving the evolution of the center of activities towards them were implemented.

scholarly journals The Effect of Connected Vehicle Environment on Global Travel Efficiency and Its Optimal Penetration Rate

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Rongjian Dai ◽  
Yingrong Lu ◽  
Chuan Ding ◽  
Guangquan Lu
Keyword(s):  
Penetration Rate ◽  
Transportation System ◽  
Transportation Systems ◽  
Information Environment ◽  
Connected Vehicle ◽  
Advantages And Disadvantages ◽  
Route Network ◽  
Travel Efficiency ◽  
The Relationship ◽  
Global Travel

The effect of connected vehicle environment on the transportation systems and the relationship between the penetration rate of connected vehicle and its efficiency are investigated in this study. An example based on the classical two-route network is adopted in this study, in which the drivers consist of two types: informed and uninformed. The advantages and disadvantages of the connected vehicle environment are analyzed, and the concentration phenomenon is proposed and found to be mitigated when only a fraction of drivers are informed. The simulation tool embodying the characteristics of the connected vehicle environment is developed using the multiagent technology. Finally, different scenarios are simulated, such as the zero-information environment, the full-information environment, and the connected vehicle environment with various penetration rates. Moreover, simulation results of the global performance of the transportation system are compared. The results show that the connected vehicle environment can efficiently improve the performance of the transportation system, while the adverse effects due to concentration rise out from the excessive informed drivers. An optimal penetration rate of the connected vehicles is found to characterize the best performance of the system. These findings can aid in understanding the effect of the connected vehicle environment on the transportation system.

scholarly journals Dynamic Route Choice Prediction Model Based on Connected Vehicle Guidance Characteristics

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Jiangfeng Wang ◽  
Jiarun Lv ◽  
Chao Wang ◽  
Zhiqi Zhang
Keyword(s):  
Prediction Model ◽  
Information Acquisition ◽  
Route Choice ◽  
Route Planning ◽  
Calibration Model ◽  
Good Prediction ◽  
Connected Vehicle ◽  
Vehicle Guidance ◽  
Simulation Scenario ◽  
The Impact

A route choice prediction model is proposed considering the connected vehicle guidance characteristics. This model is proposed to prevent the delay in the release of guidance information and route planning due to inaccurate timing predictions of the traditional guidance systems. Based on the analysis of the impact of different connected vehicle (CV) guidance strategies on traffic flow, an indexes system for CV guidance characteristics is presented. Selecting five characteristic indexes, a route choice prediction model is designed using the logistic model. A simulation scenario is established by programming different agents for controlling the flow of vehicles and for information acquisition and transmission. The prediction model is validated using the simulation scenario, and the simulation results indicate that the characteristic indexes have a significant influence on the probability of choosing a particular route. The average root mean square error (RMSE) of the prediction model is 3.19%, which indicates that the calibration model shows a good prediction performance. In the implementation of CV guidance, the penetration rate can be considered an optional index in the adjustment of the guidance effect.

scholarly journals Modeling Travel Time Reliability of Road Network Considering Connected Vehicle Guidance Characteristics Indexes

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Jiangfeng Wang ◽  
Chao Wang ◽  
Jiarun Lv ◽  
Zhiqi Zhang ◽  
Cuicui Li
Keyword(s):  
Travel Time ◽  
Road Network ◽  
Compliance Rate ◽  
Connected Vehicle ◽  
Travel Time Reliability ◽  
Improvement Rate ◽  
Explanatory Variables ◽  
Real Time Traffic ◽  
Traffic Guidance ◽  
The Impact

Travel time reliability (TTR) is one of the important indexes for effectively evaluating the performance of road network, and TTR can effectively be improved using the real-time traffic guidance information. Compared with traditional traffic guidance, connected vehicle (CV) guidance can provide travelers with more timely and accurate travel information, which can further improve the travel efficiency of road network. Five CV characteristics indexes are selected as explanatory variables including the Congestion Level (CL), Penetration Rate (PR), Compliance Rate (CR), release Delay Time (DT), and Following Rate (FR). Based on the five explanatory variables, a TTR model is proposed using the multilogistic regression method, and the prediction accuracy and the impact of characteristics indexes on TTR are analyzed using a CV guidance scenario. The simulation results indicate that 80% of the RMSE is concentrated within the interval of 0 to 0.0412. The correlation analysis of characteristics indexes shows that the influence of CL, PR, CR, and DT on the TTR is significant. PR and CR have a positive effect on TTR, and the average improvement rate is about 77.03% and 73.20% with the increase of PR and CR, respectively, while CL and DT have a negative effect on TTR, and TTR decreases by 31.21% with the increase of DT from 0 to 180 s.

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